Advanced Age and Depression are Associated with Poor Sleep Quality in Older Adults: Outpatients Setting at a Tertiary Care in Northeast Thailand
Bibliographic record
Abstract
Background: Poor sleep quality is common and related to worse health outcomes in older adults.It is thus crucial to identify and treat modifiable risk factors.Objective: To determine the factors associated with poor sleep quality in older adults in outpatient settings. Materials and Methods:A cross-sectional study was conducted between October 1, 2019 to January 31, 2022, at Srinagarind Hospital in Thailand.Subjects aged 60 years at an outpatient clinic of the internal medicine department were included.Sleep quality was evaluated by the Pittsburgh Sleep Quality Index (PSQI).Demographic data, PSQI, Patient Health Questionaire (PHQ)-9, and Montreal Cognitive Assessment (MoCA) scores were obtained.Factors associated with poor sleep quality were analyzed using stepwise backward multiple logistic regression, and results were presented as adjusted odds ratio (aOR) with 95% confidence interval (CI). Results:The study enrolled 198 subjects.Of these, the frailty occurred in 28.78%.The prevalence of poor sleep quality was 40.9%.The independent factors associated with poor sleep quality were advanced age (aOR of 1.07, 95% CI 1.01 to 1.13, p=0.04) and high PHQ-9 score (aOR of 1.49, 95% CI 1.27 to 1.80, p<0.001). Conclusion:The prevalence of older adults in outpatient settings with poor sleep quality was high.Factors associated with poor sleep quality were advanced age and depression.Screening and treating depression in older adults who have poor sleep quality may help improve their sleep quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".